Muhammad Aizat Abu Bakar
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Preferred name
Muhammad Aizat Abu Bakar
Official Name
Muhammad Aizat , Abu Bakar
Alternative Name
Bakar, M. A.A.
Bakar, Muhammad Aizat Abu
Bakar, M. A.Abu
Bin Abu Bakar, Muhammad Aizat
Main Affiliation
Scopus Author ID
57190940268
Researcher ID
EMX-4423-2022

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Fabrication of mandible fracture plate by indirect additive manufacturing

2017-10-29 , Muhammad Aizat Abu Bakar , Shah Fenner Khan Mohamad Khan

Bone fracture is a serious skeletal injury due to accidents and fragility of the bones at a certain age. In order to accelerate fracture healing process, fracture bone plate is use to hold the fracture segment for more stability. The purpose of this study is to fabricate mandibular fracture plate by using indirect additive manufacturing methods in order to reduce time taken during bending and shaping the fracture fixation plate that conform to the anatomy of the fractured bone site. The design and analysis of the plates are performed using CATIA and ANSYS software. The 3D-CAD data were sent to an additive manufacturing machine (fused filament fabricated) to generate master pattern using PLA and the mould were fabricated using Plaster of Paris. A melt ZAMAK 3 was poured directly into the moulds, and left it until completely harden. 3point bending test was performed on the prototype plate using universal testing machine. Stress-strain curve shows the graph exhibited a linear relationship of stress-strain up to a strain value of 0.001. Specimens give a maximum yielding stress and then break before the conventional deflection. Since the maximum flexural stress and the breaking stress are far apart with a plateau stating at strain value of 0.003mm/mm in most specimens, the specimen's failure types are considered plastic failure mode. The average thickness and width are 1.65mm and 2.18mm respectively. The flexural modulus and flexural strength are 189.5GPa and 518.1MPa, respectively.

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IoT-based Carbon Monoxide (CO) Real-Time Warning System Application in Vehicles

2021-12-01 , Kamarudin A.A.A. , Nurul Syahirah Khalid , Ismail Ishaq Ibrahim , Muhammad Aizat Abu Bakar , Mahadi M.Z. , Shazmin Aniza Abdul Shukor , Sukhairi Sudin , Mohd Zamri Hasan , Humairah Mansor

The project is about develop a system and application for detect the presence of Carbon Monoxide(CO) in car, since recently there are many cases of drowning while sleeping in car due to inhaling CO. The build system are able to detect the presence of CO and provide warning about level of CO to the users. It uses Blynk application to monitors level of CO inside the vehicle, MQ-9 gas sensor as the input sensor, ESP 8266 as medium to send data to the application via IoT-based and the level concentration of CO is displayed on the LCD in real-time displayed. For the output, it has 3 different condition based on the level concentration of CO. This project has been testing in six different situation. Based on the result, ambience air and in car with open window situation have lowest of CO level. Meanwhile, the highest of CO level is detect in smoke that are produced from fuel combustion of the car exhaust at distance 5 cm. Additionally, Principal Component Analysis (PCA) is used to analysed the ability of this system in clustering for each situation. As a result, PCA have clearly clustering data for every situation with the value of PC1 is 71.82% and PC2 is 28.18%, hence it is verified that the build system is able to applied in detecting the presence of CO. This project is believed able in helping to reduce the numbers of cases people drowning while sleeping due to inhaling CO in the car.

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Cloud-based System for University Laboratories Air Monitoring

2020-09-21 , Abu Hassan Abdullah , Sukhairi Sudin , Mustafa M.H. , Fathinul Syahir Ahmad Sa'ad , Khairul Azwan Ismail , Muhammad Aizat Abu Bakar , Mohamed Elshaikh Elobaid Said Ahmed , Abdul Ghapar Ahmad , Zahari Awang Ahmad , Sara Yasina Yusuf

Indoor air such as house, shopping complex, hospital, university, office and hotel should be monitor for human safety and wellbeing. These closed areas are prone to harmful air pollutants i.e. allergens, smoke, mold, particles radon and hazardous gas. Laboratories in university are special room in which workers (student, technician, teaching/research assistants, researcher and lecturer) conduct their works and experiment. The activities and the environment will generate specific air pollutant which concentration depending to their parameters. Anyone in the environment that exposure to these pollutants may affect safety and health issue. This paper proposes a study of development of a cloud-based electronic nose system for university laboratories air monitoring. The system consists of DSP33-based electronic nose (e-nose) as nodes which measure main indoor air pollutant along with two thermal comfort variables, temperature and relative humidity. The e-noses are placed at five different laboratories for acquiring data in real time. The data will be sent to a web server and the cloud-based system will process, analyse using Neuro-Fuzzy classifier and display on a website in real time. The system will monitor the laboratories air pollutants and thermal comfort by predict the pollutant concentration and dispersion in the area i.e. Air Pollution Index (API). In case of air hazard safety (e.g., gas spills detection and pollution monitoring), the system will alert the security by activate an alarm and through e-mail. The website will display the API of the area in real-time. Results show that the system performance is good and can be used to monitor the air pollutant in the university laboratories.

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IoT-based Carbon Monoxide (CO) Real-Time Warning System Application in Vehicles

2021-12-01 , Kamarudin A.A.A. , Nurul Syahirah Khalid , Ibrahim I.I. , Muhammad Aizat Abu Bakar , Mahadi M.Z. , Shukor S.A.A. , Sukhairi Sudin , Hasan M.Z. , Mansor H.

The project is about develop a system and application for detect the presence of Carbon Monoxide(CO) in car, since recently there are many cases of drowning while sleeping in car due to inhaling CO. The build system are able to detect the presence of CO and provide warning about level of CO to the users. It uses Blynk application to monitors level of CO inside the vehicle, MQ-9 gas sensor as the input sensor, ESP 8266 as medium to send data to the application via IoT-based and the level concentration of CO is displayed on the LCD in real-time displayed. For the output, it has 3 different condition based on the level concentration of CO. This project has been testing in six different situation. Based on the result, ambience air and in car with open window situation have lowest of CO level. Meanwhile, the highest of CO level is detect in smoke that are produced from fuel combustion of the car exhaust at distance 5 cm. Additionally, Principal Component Analysis (PCA) is used to analysed the ability of this system in clustering for each situation. As a result, PCA have clearly clustering data for every situation with the value of PC1 is 71.82% and PC2 is 28.18%, hence it is verified that the build system is able to applied in detecting the presence of CO. This project is believed able in helping to reduce the numbers of cases people drowning while sleeping due to inhaling CO in the car.

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Parameters tuning for enhanced automated guided vehicle navigation in ROS/gazebo simulation environment

2025 , Muhammad Aizat Abu Bakar , Nurakasyah Qistina , Kamarulzaman Kamarudin , Heng Han , Hafizul Imran , Wan Rahiman

Automated Guided Vehicle (AGV) robot, a type of ground transportation vehicle that follows a predetermined path, is now in high demand in industrial operations and among researchers. AGV robot may improve it carrying capacity in the delivery operation through consistent and safe behaviour. The main challenge is in its navigation system when obstacles appear unexpectedly on its desired path, its limited abilities make it unable to avoid obstacles that would interfere with the smooth operation and decrease the quality of time. The aim of this research work is to present a tuning parameter of algorithms, namely the Pure Pursuit based on coordinates look-ahead distance for navigation and the Vector Field Histogram based on safety distance for avoiding obstacles. Robot Operating System (ROS) platform and Gazebo simulator environment are used to simulate the simulation testing for algorithms. According to the test results, the combination of these algorithms produced promising outcomes by demonstrating the AGV's capability to manoeuvre along a predetermined path, avoid obstacles, and return to its original path in order to reach its goal position.

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2D LiDAR based reinforcement learning for Multi-Target path planning in unknown environment

2023 , Nasr Abdalmanan , Kamarulzaman Kamarudin , Muhammad Aizat Abu Bakar , Mohd Hafiz Fazalul Rahiman , Ammar Zakaria , Syed Muhammad Mamduh Syed Zakaria , Latifah Munirah Kamarudin

Global path planning techniques have been widely employed in solving path planning problems, however they have been found to be unsuitable for unknown environments. Contrarily, the traditional Q-learning method, which is a common reinforcement learning approach for local path planning, is unable to complete the task for multiple targets. To address these limitations, this paper proposes a modified Q-learning method, called Vector Field Histogram based Q-learning (VFH-QL) utilized the VFH information in state space representation and reward function, based on a 2D LiDAR sensor. We compared the performance of our proposed method with the classical Q-learning method (CQL) through training experiments that were conducted in a simulated environment with a size of 400 square pixels, representing a 20-meter square map. The environment contained static obstacles and a single mobile robot. Two experiments were conducted: experiment A involved path planning for a single target, while experiment B involved path planning for multiple targets. The results of experiment A showed that VFH-QL method had 87.06% less training time and 99.98% better obstacle avoidance compared to CQL. In experiment B, VFH-QL method was found to have an average training time that was 95.69% less than that of the CQL method and 83.99% better path quality. The VFH-QL method was then evaluated using a benchmark dataset. The results indicated that the VFH-QL exhibited superior path quality, with efficiency of 94.89% and improvements of 96.91% and 96.69% over CQL and SARSA in the task of path planning for multiple targets in unknown environments.

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The Effect Of Anthracene Group Substitution Of Disubstituted Chalcone Derivative Featuring Terephthalaldehyde Π-Linker On Non-Linear Optical (Nlo) Characteristic

2023-01-01 , Shuaib N.N. , Daud A.I. , Arshad S. , Muhammad Aizat Abu Bakar , Khairul W.M.

In past years, the π-conjugated system has attracted much attention as a promising material for developing and manufacturing the next generation of organic electronics made of synthesised organic compounds. Chalcone, having the π-conjugated systems in their molecular structures and the unique α, β-unsaturated ketone structural, have gained much attraction due to their potential use in optoelectronics applications like organic light emitting diode (OLED). By altering the molecular structure, the physical and chemical properties of chalcone derivatives can be tailored to the application needed. In recent years, chemists have produced many types of π-conjugated molecules to acquire excellent luminescence characteristics from organic compounds, and such structures typically lead to intense colour and excellent photoluminescence. In this study, a disubstituted chalcone derivative featuring terephthalaldehyde (N1A) as a π-linker with anthracene as donating group substitution has been synthesised through the Claisen-Schmidt condensation reaction. The synthesised compound has been characterised using Fourier Transform Infrared spectroscopy (FTIR) and UV-Visible analysis. Density functional theory (DFT) computations are executed to evaluate the effect of anthracene as an electron donating substitution on NLO properties of disubstituted chalcone derivative. NLO responses of this disubstituted chalcone derivative disclose that the chalcone molecular framework exhibit an important characteristic for further application as OLED emitting material.

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Electronic Nose Testing for Confined Space Application Utilizes Principal Component Analysis and Support Vector Machine

2020-12-18 , Muhammad Aizat Abu Bakar , Abu Hassan Abdullah , Wan Azani Wan Mustafa , Zol Bahri Razali , Syahrul Affandi Saidi , Mohamed Mydin Hj M.Abdul Kader , Aman M.N.S.B.S.

A confined space has a limited space for entry and exit but it is large enough for workers to enter and perform work inside. It is not designed for continuous occupancy because it can contribute atmospheric hazards accidents that threaten the worker safety and industry progress. In this work, we reported the testing an instrument to assist workers for atmosphere testing during pre-entry. An electronic nose (e-nose) using specific sensor arrays is the integration between hardware and software that able to sense different concentrations of gases in an air sample using pattern recognition techniques. The instrument utilizes multivariate statistical analysis which is Principal Component Analysis (PCA) for discriminate the different concentrations of gases and the Support Vector Machine (SVM) to classify the acquired data from the air sample. The instrument was successfully tested using diesel, gasoline, petrol and thinner. The results show that the instrument able to discriminate an air sample using PCA with total variation for 99.94%, while the classifier success rate for SVM indicates at 98.21% for train performance and 95.83% for test performance. This will contribute significantly to acquiring a new and alternative method of using the instrument for monitoring the atmospheric hazards in confined space to ensure the safety of workers during work progress in a confined space.

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Home automation system for security and temperature control using microcontroller based with smartphone applications

2021-05-03 , Muhammad Aizat Abu Bakar , Fazreen Mohd Yusoff , Aminudin Anuar , Muhammad Nur Aiman Uda , Asyraf Hakimi Abu Bakar , Muhammad Nur Afnan Uda , Mohamed K. Sulaiman

In Malaysia, the El-Nino phenomenon happen in 2016 was caused the used of home appliances increasing including air-conditioner, fan and air cooler which are used frequently compared to other appliances. This report presents prototype development System for Security and Temperature Control using Microcontroller Based with Smartphone Application. The system has beneficial to reduce human labour besides energy saving and designed for special purposes which can easily maintain the temperature in sorrounding home. The system used several sensors for input parts including LM35 for temperature sensor and Passive Infra-Red (PIR) sensor for motion detector. For security system, the Radio-frequency Identification (RFID) has been used as security input user identification. A microcontroller arduino uno type is used as the system brain in the process part. In outputs part, servo motor has been used as door application while Light-Emitting Diode (LED) and buzzer as indicators when RFID is in use. A smartphone application is implemented in the system which allows the user to control a device remotely including home appliances through Bluetooth module. All data will display in Liquid Crystal Display (LCD) as user reference.

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Development of portable electronic nose for monitoring the atmospheric hazards in confined space

2018 , Muhammad Aizat Abu Bakar

This thesis discussed the development of electronic nose (e-nose) for monitoring the atmospheric hazards in a confined space. A confined space is large enough for workers to enter and perform work. It has a limited means of entry or exit and is not designed for continuous occupancy. It can contribute towards atmospheric hazards accidents that threaten the worker safety and industry progress. The most critical atmospheric hazards are too high or low oxygen in the atmosphere or atmospheres that contain flammable or toxic gases. Current technology to monitor the atmospheric hazards is applied before entering confined spaces called pre-entry by using a gas detector. This study aims to develop an instrument to assist workers during pre-entry for atmosphere testing. E-nose is the integration between hardware and software that can identify and classify different concentrations of gases in an air sample using pattern recognition techniques. The developed instrument using specific sensor arrays which were identified based on main hazardous gasses effective value. The temperature and humidity rates are also measured. The instrument utilizes multivariate statistical analysis that is Principal Component Analysis (PCA) for discriminate the different concentrations of gases. The Support Vector Machine (SVM) and Artificial Neural Network (ANN) that is Radial Basis Function (RBF) Network are used to classify the acquired data from the air sample. This will increase the instrument capability while the portability will minimize the size and operational complexity as well as increase user friendliness. The instrument was successfully developed, tested and calibrated using fixed concentrations of gases samples. The results proved that the developed instrument is able to discriminate an air sample using PCA with total variation for 99.42%, while the classifier success rate for SVM and RBF Network indicates at 99.28% for train performance and 98.33% for test performance. This will contribute significantly to acquiring a new and alternative method of using the instrument for monitoring the atmospheric hazards in confined space. This will ensure the safety of workers during work progress in a confined space.

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